摘要
本文基于CARIMA模型提出了一种简单的隐式广义预测自校正控制算法。它避免了在线求解Dioaphantine方程;利用并列预测器间的特点,直接辨识输出预测器中的参数,并针对广义预测控制问题,在整个预测时域和控制时域,对输入幅值施加了约束;在此基础上以二次规划作为滚动优化策略,进行计算机仿真,获得预测控制信息和输出信息;然后采用加权控制律,不仅使预测信息得以充分利用,而且使系统的性能得到明显改善。
In this paper, a simple implicit generalized predictive self--tuning control algorithm based on CARIMA model is presented. It avoids solving Dioaphantine equation on-line. The parameters of the output predictive equation are directly identified by the characteristic of the parallel predictors, and inputs are constrained by focusing on the generalized predictive control and in the whole of prediction horizon and control horizon. When the inputs are constrained, if the quadratic term of manipulative variable of the criterion function is deleted, calculation will be simple. With this understanding, quadratic program is taken as the optimization, which can be simulated by computer. The presented algorithm can get the information about the predictive control and outputs. Then the using of weighted control regulation not only makes full use of the predictive information, but also improves the criterion greatly.
出处
《系统仿真学报》
CAS
CSCD
2004年第7期1533-1535,共3页
Journal of System Simulation
基金
山西省青年科技研究基金项目(20011017)
关键词
广义预测控制
受限
加权控制律
隐式算法
发动机
generalized predictive control
constrains
weighted control regulation
implicit arithmetic
engine
